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Enterprise Data Strategy

Data Literacy Bootcamp

Published by O'Reilly Media, Inc.

Intermediate content levelIntermediate

How to inspire business decisions with data

Data is becoming increasingly embedded into every strategy and business decision. We’ve moved from a world where business experts made decisions based on their experience to a world where data drives (or at least informs) nearly every strategy. As data production has exploded and continues to grow, it’s increasingly important for companies to build their data strategy and level up their data literacy. This trend has created the need for individuals to be able to read, analyze, and communicate with data.

Join expert Sarah Nooravi to get the tools you need to work with data effectively, ask the right questions (of the data and your stakeholders), and develop a strong, data-driven narrative that can help inform strategy decisions. At the end of this course, you’ll be equipped to tackle data problems more confidently and develop more decisive solutions.

Week 1: Foundations of Data Literacy, the Analytics Toolkit, and Intro to Excel

Week 2: Data Cleaning, Intermediate Excel, and Visual Basics

Week 3: Effective Storytelling Techniques and Visual Best Practices

NOTE: With today’s registration, you’ll be signed up for all three sessions. Although you can attend any of the sessions individually, we recommend participating in all three weeks.

What you’ll learn and how you can apply it

  • Tell more effective stories with data
  • Create and use simple and advanced Excel formulas
  • Create workbooks/sheets, enter data, filter, and sort
  • Apply visual design techniques and best practices to multiple types of visualizations

This live event is for you because...

  • You want to level up your data literacy skills to expand your impact in your current role.
  • You want to learn best practices for effectively driving strategy through data.
  • You want to gain familiarity with Excel.

Prerequisites

  • A computer with any version of Excel installed (if you don’t already have it, you can sign up for a free 30-day trial)

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Week 1: Foundations of Data Literacy, the Analytics Toolkit, and Intro to Excel

Getting started (15 minutes)

  • Presentation: What is data and where does it come from?; big data trends and why data literacy is important; how data is created; small data versus big data

Foundational concepts—Part I (45 minutes)

  • Presentation: Basic data terminology; descriptive statistics and distributions; summaries and visualizations
  • Q&A
  • Break

Foundational concepts—Part II (40 minutes)

  • Presentation: Statistical sampling; bias and variance; correlation
  • Q&A

Open source data (5 minutes)

  • Presentation: Where to find data online; review of open source data (Data.gov, Dataset Search, and Kaggle)

Excel basics—Part I (15 minutes)

  • Presentation: Getting started with Excel; gaining familiarity with the interface; open workbook; sample dataset review
  • Break

Excel basics—Part II (10 minutes)

  • Presentation: Changing data types and formats; creating simple formulas; built-in aggregations (sums/averages)

Filtering the data (30 minutes)

  • Presentation: Creating a filter; comparing and combining filters; date filters, continuous versus discrete filters; displaying filters for user access; relevant values and filter customization

Sorting data (10 minutes)

  • Presentation: Basic sorts; conditional sorts (sorts based on something else)
  • Hands-on exercise: Use filters to display data from last three years

Wrap-Up and Q&A (10 minutes)

Week 2: Data Cleaning, Intermediate Excel, and Visual Basics

Data cleaning (35 minutes)

  • Presentation: Handling missing values; imputation; handling outliers—when to remove, when to keep, when to impute

Transformations (25 minutes)

  • Presentation: When to transform; log transformations; normality
  • Q&A
  • Break

Advanced formulas (35 minutes)

  • Presentation: SUMIF, VLOOKUP, INDEX, and MATCH functions
  • Exercise

Pivot tables (25 minutes)

  • Presentation: SUMIF, VLOOKUP, INDEX, and MATCH functions
  • Exercise
  • Q&A
  • Break

Joins (30 minutes)

  • Presentation: Types of joins (outer, inner, left); common pitfalls when working with joins; data QA
  • Exercise

Visual basics (20 minutes)

  • Presentation: Crosstabs; scatter plots; line charts; bar charts

Wrap-Up and Q&A (10 minutes)

Week 3: Effective Storytelling Techniques and Visual Best Practices

Hands-on visual basics (10 minutes)

  • Exercise: Given a dataset, develop a visual that best represents that dataset
  • Group discussion: Review exercise

Soft skills in analytics (10 minutes)

  • Presentation: What soft skills will do for you and your career

Storytelling with data (40 minutes)

  • Presentation: Defining the problem; understanding what data you have access to and any limitations; understanding your audience; exploratory versus explanatory visuals; value-add thinking/be actionable
  • Q&A
  • Break

Visual best practices (20 minutes)

  • Presentation: Avoid clutter; add color; color theory; don’t manipulate the visuals; simple versus complex; using text appropriately

From good to great (35 minutes)

  • Group discussion: Real-world examples of good and bad visuals and ways they can be improved
  • Q&A
  • Break

End-to-end example (55 minutes)

  • Presentation: Present problem; define problem and tasks/metrics; find dataset; clean/transform; define audience and choose best visual

Wrap-Up and Q&A (10 minutes)

Your Instructor

  • Sarah Nooravi

    Sarah Nooravi works as a lead on the revenue strategy team at Snapchat and recently served as product manager for two data projects for the city of Los Angeles. She’s also worked in the entertainment and gaming industries. Sarah has garnered a following on LinkedIn through her efforts to give back to the community—hosting meetups, blogging, presenting at conferences, and leading organizations like WiBD and GLAD. She has a bachelor’s degree in mathematics and economics and a master’s in mechanical engineering, both from the University of California, Los Angeles.